2020 |
Rocha, Luis Mateus; Singh, Vikramjit; Esch, Markus; Lenaerts, Tom; Liljeros, Fredrik; Thorson, Anna Dynamic contact networks of patients and MRSA spread in hospitals Journal Article Scientific reports, 10 (1), 2020, (DOI: 10.1038/s41598-020-66270-9). @article{info:hdl:2013/308993, title = {Dynamic contact networks of patients and MRSA spread in hospitals}, author = {Luis Mateus Rocha and Vikramjit Singh and Markus Esch and Tom Lenaerts and Fredrik Liljeros and Anna Thorson}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/308993}, year = {2020}, date = {2020-01-01}, journal = {Scientific reports}, volume = {10}, number = {1}, note = {DOI: 10.1038/s41598-020-66270-9}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Colaprico, Antonio; Olsen, Catharina; Bailey, Matthew; Odom, Gabriel G J; Terkelsen, Thilde; Silva, Tiago Chedraoui; Olsen, André Vidas; Cantini, Laura; Zinovyev, Andrey; Barillot, Emmanuel; Noushmehr, Houtan; Bertoli, Gloria; Castiglioni, Isabella; Cava, Claudia; Bontempi, Gianluca; Chen, Xi Steven; Papaleo, Elena Interpreting pathways to discover cancer driver genes with Moonlight Journal Article Nature communications, 11 (1), 2020, (DOI: 10.1038/s41467-019-13803-0). @article{info:hdl:2013/301750, title = {Interpreting pathways to discover cancer driver genes with Moonlight}, author = {Antonio Colaprico and Catharina Olsen and Matthew Bailey and Gabriel G J Odom and Thilde Terkelsen and Tiago Chedraoui Silva and André Vidas Olsen and Laura Cantini and Andrey Zinovyev and Emmanuel Barillot and Houtan Noushmehr and Gloria Bertoli and Isabella Castiglioni and Claudia Cava and Gianluca Bontempi and Xi Steven Chen and Elena Papaleo}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/301750}, year = {2020}, date = {2020-01-01}, journal = {Nature communications}, volume = {11}, number = {1}, note = {DOI: 10.1038/s41467-019-13803-0}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Caro, Fabrizio De; Stefani, Jacopo De; Bontempi, Gianluca; Vaccaro, Alfredo A; Villacci, Domenico D Robust Assessment of Short-Term Wind Power Forecasting Models on Multiple Time Horizons Journal Article Technology and Economics of Smart Grids and Sustainable Energy, 5 (1), 2020, (DOI: 10.1007/s40866-020-00090-8). @article{info:hdl:2013/314435, title = {Robust Assessment of Short-Term Wind Power Forecasting Models on Multiple Time Horizons}, author = {Fabrizio De Caro and Jacopo De Stefani and Gianluca Bontempi and Alfredo A Vaccaro and Domenico D Villacci}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/314435}, year = {2020}, date = {2020-01-01}, journal = {Technology and Economics of Smart Grids and Sustainable Energy}, volume = {5}, number = {1}, note = {DOI: 10.1007/s40866-020-00090-8}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
"e, Ma; Demetter, Pieter; Wind, Roland De; Galdon, Maria Gomez; Velde, Sylvie Vande; Lens, Gaspard; Craciun, Ligia; Deleruelle, Amélie; Larsimont, Denis; Lenaerts, Tom; Sclafani, Francesco; Deleporte, Amélie; Donckier, Vincent; Hendlisz, Alain; Vandeputte, Caroline Infiltrative tumour growth pattern correlates with poor outcome in oesophageal cancer. Journal Article BMJ open gastroenterology, 7 (1), 2020, (DOI: 10.1136/bmjgast-2020-000431). @article{info:hdl:2013/312667, title = {Infiltrative tumour growth pattern correlates with poor outcome in oesophageal cancer.}, author = {Ma{"e}lle Anciaux and Pieter Demetter and Roland De Wind and Maria Gomez Galdon and Sylvie Vande Velde and Gaspard Lens and Ligia Craciun and Amélie Deleruelle and Denis Larsimont and Tom Lenaerts and Francesco Sclafani and Amélie Deleporte and Vincent Donckier and Alain Hendlisz and Caroline Vandeputte}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/312667}, year = {2020}, date = {2020-01-01}, journal = {BMJ open gastroenterology}, volume = {7}, number = {1}, note = {DOI: 10.1136/bmjgast-2020-000431}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Grujić, Jelena; Lenaerts, Tom Do people imitate when making decisions? Evidence from a spatial Prisoner's Dilemma experiment: Do people imitate when making decisions Journal Article Royal Society open science, 7 (7), 2020, (DOI: 10.1098/rsos.200618). @article{info:hdl:2013/313051, title = {Do people imitate when making decisions? Evidence from a spatial Prisoner's Dilemma experiment: Do people imitate when making decisions}, author = {Jelena Grujić and Tom Lenaerts}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/313051}, year = {2020}, date = {2020-01-01}, journal = {Royal Society open science}, volume = {7}, number = {7}, note = {DOI: 10.1098/rsos.200618}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Orlando, Gabriele; Raimondi, Daniele; Kagami, Luciano Porto; Vranken, Wim ShiftCrypt: a web server to understand and biophysically align proteins through their NMR chemical shift values Journal Article Nucleic acids research, 48 (W1), pp. W36-W40, 2020, (DOI: 10.1093/nar/gkaa391). @article{info:hdl:2013/312301, title = {ShiftCrypt: a web server to understand and biophysically align proteins through their NMR chemical shift values}, author = {Gabriele Orlando and Daniele Raimondi and Luciano Porto Kagami and Wim Vranken}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/312301}, year = {2020}, date = {2020-01-01}, journal = {Nucleic acids research}, volume = {48}, number = {W1}, pages = {W36-W40}, note = {DOI: 10.1093/nar/gkaa391}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Lorenzo, Ramiro; Onizuka, Michiho; Defrance, Matthieu; Laurent, Patrick Combining single-cell RNA-sequencing with a molecular atlas unveils new markers for Caenorhabditis elegans neuron classes. Journal Article Nucleic acids research, 2020, (DOI: 10.1093/nar/gkaa486). @article{info:hdl:2013/309336, title = {Combining single-cell RNA-sequencing with a molecular atlas unveils new markers for Caenorhabditis elegans neuron classes.}, author = {Ramiro Lorenzo and Michiho Onizuka and Matthieu Defrance and Patrick Laurent}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/309336}, year = {2020}, date = {2020-01-01}, journal = {Nucleic acids research}, note = {DOI: 10.1093/nar/gkaa486}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Lipski, D; Foucart, Vincent; Dewispelaere, Remi; Caspers, Laure; Defrance, Matthieu; Bruyns, Catherine; Willermain, Francois Retinal endothelial cell phenotypic modifications during experimental autoimmune uveitis: A transcriptomic approach Journal Article BMC ophthalmology, 20 (1), 2020, (DOI: 10.1186/s12886-020-1333-5). @article{info:hdl:2013/305060, title = {Retinal endothelial cell phenotypic modifications during experimental autoimmune uveitis: A transcriptomic approach}, author = {D Lipski and Vincent Foucart and Remi Dewispelaere and Laure Caspers and Matthieu Defrance and Catherine Bruyns and Francois Willermain}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/305060}, year = {2020}, date = {2020-01-01}, journal = {BMC ophthalmology}, volume = {20}, number = {1}, note = {DOI: 10.1186/s12886-020-1333-5}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Duerinckx, Sarah; Jacquemin, Valérie; Drunat, Séverine; Vial, Yoann; Passemard, Sandrine; Perazzolo, Camille; Massart, Annick; Soblet, Julie; Racapé, Judith; Desmyter, Laurence; Badoer, Cindy; Papadimitriou, Sofia; "e, Yann-A; Lefort, Anne; Libert, Frédérick; Maertelaer, Viviane De; Rooman, Marianne; Costagliola, Sabine; Verloes, Alain; Lenaerts, Tom; Pirson, Isabelle; Abramowicz, Marc Digenic inheritance of human primary microcephaly delineates centrosomal and non centrosomal pathways. Journal Article Human mutation, 41 (2), pp. 512-524, 2020, (DOI: 10.1002/humu.23948). @article{info:hdl:2013/296188, title = {Digenic inheritance of human primary microcephaly delineates centrosomal and non centrosomal pathways.}, author = {Sarah Duerinckx and Valérie Jacquemin and Séverine Drunat and Yoann Vial and Sandrine Passemard and Camille Perazzolo and Annick Massart and Julie Soblet and Judith Racapé and Laurence Desmyter and Cindy Badoer and Sofia Papadimitriou and Yann-A{"e}l Le Borgne and Anne Lefort and Frédérick Libert and Viviane De Maertelaer and Marianne Rooman and Sabine Costagliola and Alain Verloes and Tom Lenaerts and Isabelle Pirson and Marc Abramowicz}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/296188}, year = {2020}, date = {2020-01-01}, journal = {Human mutation}, volume = {41}, number = {2}, pages = {512-524}, note = {DOI: 10.1002/humu.23948}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
2019 |
Jansen, Maarten Multiscale local polynomials for unequispaced data processing Miscellaneous 2019, (Conference: FNRS contact group study day ``Wavelets and applications''). @misc{info:hdl:2013/297566, title = {Multiscale local polynomials for unequispaced data processing}, author = {Maarten Jansen}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/297566}, year = {2019}, date = {2019-01-01}, note = {Conference: FNRS contact group study day ``Wavelets and applications''}, keywords = {}, pubstate = {published}, tppubtype = {misc} } |
Jansen, Maarten Multiscale local polynomial estimation from highly irregular data Miscellaneous 2019, (Language of publication: fr). @misc{info:hdl:2013/297565, title = {Multiscale local polynomial estimation from highly irregular data}, author = {Maarten Jansen}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/297565}, year = {2019}, date = {2019-01-01}, note = {Language of publication: fr}, keywords = {}, pubstate = {published}, tppubtype = {misc} } |
Claeskens, G; Jansen, Maarten Discussion on ``Model Confidence Bounds for Variable Selection'' by Yang Li, Yuetian Luo, Davide Ferrari, Xiaonan Hu, and Yichen Qin Journal Article Biometrics, 75 (2), pp. 404-406, 2019, (Language of publication: en). @article{info:hdl:2013/280731, title = {Discussion on ``Model Confidence Bounds for Variable Selection'' by Yang Li, Yuetian Luo, Davide Ferrari, Xiaonan Hu, and Yichen Qin}, author = {G Claeskens and Maarten Jansen}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/280731}, year = {2019}, date = {2019-01-01}, journal = {Biometrics}, volume = {75}, number = {2}, pages = {404-406}, note = {Language of publication: en}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Esteve, Mariana Igoillo; Oliveira, Ana Filipa Martins; Cosentino, Cristina; Fantuzzi, Federica; Demarez, Céline; Toivonen, Sanna; Hu, Amelie; Chintawar, Satyan; Lopes, Miguel; Pachera, Nathalie; Cai, Ying; Abdulkarim, Baroj; Rai, Myriam; Marselli, Lorella; Marchetti, Piero; Tariq, Mohammad; Jonas, Jean-Christophe JJC; Boscolo, Marina; Pandolfo, Massimo; Eizirik, Decio L; Cnop, Miriam Exenatide induces frataxin expression and improves mitochondrial function in Friedreich ataxia. Journal Article JCI insight, 2019, (DOI: 10.1172/jci.insight.134221). @article{info:hdl:2013/300907, title = {Exenatide induces frataxin expression and improves mitochondrial function in Friedreich ataxia.}, author = {Mariana Igoillo Esteve and Ana Filipa Martins Oliveira and Cristina Cosentino and Federica Fantuzzi and Céline Demarez and Sanna Toivonen and Amelie Hu and Satyan Chintawar and Miguel Lopes and Nathalie Pachera and Ying Cai and Baroj Abdulkarim and Myriam Rai and Lorella Marselli and Piero Marchetti and Mohammad Tariq and Jean-Christophe JJC Jonas and Marina Boscolo and Massimo Pandolfo and Decio L Eizirik and Miriam Cnop}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/300907}, year = {2019}, date = {2019-01-01}, journal = {JCI insight}, note = {DOI: 10.1172/jci.insight.134221}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Orlando, Gabriele; Raimondi, Daniele; Vranken, Wim F Auto-encoding NMR chemical shifts from their native vector space to a residue-level biophysical index Journal Article Nature communications, 10 (1), 2019, (DOI: 10.1038/s41467-019-10322-w). @article{info:hdl:2013/289767, title = {Auto-encoding NMR chemical shifts from their native vector space to a residue-level biophysical index}, author = {Gabriele Orlando and Daniele Raimondi and Wim F. Vranken}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/289767}, year = {2019}, date = {2019-01-01}, journal = {Nature communications}, volume = {10}, number = {1}, note = {DOI: 10.1038/s41467-019-10322-w}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Raimondi, Daniele; Orlando, Gabriele; Vranken, Wim; Moreau, Yves Exploring the limitations of biophysical propensity scales coupled with machine learning for protein sequence analysis Journal Article Scientific reports, 9 (1), 2019, (DOI: 10.1038/s41598-019-53324-w). @article{info:hdl:2013/296968, title = {Exploring the limitations of biophysical propensity scales coupled with machine learning for protein sequence analysis}, author = {Daniele Raimondi and Gabriele Orlando and Wim Vranken and Yves Moreau}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/296968}, year = {2019}, date = {2019-01-01}, journal = {Scientific reports}, volume = {9}, number = {1}, note = {DOI: 10.1038/s41598-019-53324-w}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Mishima, Yuichi; Brueckner, Laura; Takahashi, Saori; Kawakami, Toru; Otani, Junji; Shinohara, Akira; Takeshita, Kohei; Garvilles, Ronald Garingalao; Watanabe, Mikio; Sakai, Norio; Takeshima, Hideyuki; Nachtegael, Charlotte; Nishiyama, Atsuya; Nakanishi, Makoto; Arita, Kyohei; Nakashima, Kinichi; Hojo, Hironobu; Suetake, Isao Enhanced processivity of Dnmt1 by mono‐ubiquitinated histone H3 Journal Article Genes to cells, 2019, (DOI: 10.1111/gtc.12732). @article{info:hdl:2013/296160, title = {Enhanced processivity of Dnmt1 by mono‐ubiquitinated histone H3}, author = {Yuichi Mishima and Laura Brueckner and Saori Takahashi and Toru Kawakami and Junji Otani and Akira Shinohara and Kohei Takeshita and Ronald Garingalao Garvilles and Mikio Watanabe and Norio Sakai and Hideyuki Takeshima and Charlotte Nachtegael and Atsuya Nishiyama and Makoto Nakanishi and Kyohei Arita and Kinichi Nakashima and Hironobu Hojo and Isao Suetake}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/296160}, year = {2019}, date = {2019-01-01}, journal = {Genes to cells}, note = {DOI: 10.1111/gtc.12732}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Istaces, Nicolas; Splittgerber, Marion; Silva, Viviana Lima; Nguyen, Muriel; Thomas, Séverine; Le, Aurore; Achouri, Younes; Calonne, Emilie; Defrance, Matthieu; cc, Fran; Goriely, Stanislas; Azouz, Abdulkader EOMES interacts with RUNX3 and BRG1 to promote innate memory cell formation through epigenetic reprogramming Journal Article Nature communications, 10 (1), 2019, (DOI: 10.1038/s41467-019-11233-6). @article{info:hdl:2013/294385, title = {EOMES interacts with RUNX3 and BRG1 to promote innate memory cell formation through epigenetic reprogramming}, author = {Nicolas Istaces and Marion Splittgerber and Viviana Lima Silva and Muriel Nguyen and Séverine Thomas and Aurore Le and Younes Achouri and Emilie Calonne and Matthieu Defrance and Fran{cc}ois Fuks and Stanislas Goriely and Abdulkader Azouz}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/294385}, year = {2019}, date = {2019-01-01}, journal = {Nature communications}, volume = {10}, number = {1}, note = {DOI: 10.1038/s41467-019-11233-6}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Thorsson, Vesteinn; Colaprico, Antonio; others, Erratum: The Immune Landscape of Cancer (Immunity (2018) 48(4) (812–830.e14), (S1074761318301213), (10.1016/j.immuni.2018.03.023)) Journal Article Immunity, 51 (2), pp. 411-412, 2019, (DOI: 10.1016/j.immuni.2019.08.004). @article{info:hdl:2013/299167, title = {Erratum: The Immune Landscape of Cancer (Immunity (2018) 48(4) (812–830.e14), (S1074761318301213), (10.1016/j.immuni.2018.03.023))}, author = {Vesteinn Thorsson and Antonio Colaprico and others}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/299167}, year = {2019}, date = {2019-01-01}, journal = {Immunity}, volume = {51}, number = {2}, pages = {411-412}, note = {DOI: 10.1016/j.immuni.2019.08.004}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Versbraegen, Nassim; Fouché, Aziz; Nachtegael, Charlotte; Papadimitriou, Sofia; Gazzo, Andrea; Smits, Guillaume; Lenaerts, Tom Using game theory and decision decomposition to effectively discern and characterise bi-locus diseases Journal Article Artificial intelligence in medicine, 99 , 2019, (DOI: 10.1016/j.artmed.2019.06.006). @article{info:hdl:2013/292462, title = {Using game theory and decision decomposition to effectively discern and characterise bi-locus diseases}, author = {Nassim Versbraegen and Aziz Fouché and Charlotte Nachtegael and Sofia Papadimitriou and Andrea Gazzo and Guillaume Smits and Tom Lenaerts}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/292462}, year = {2019}, date = {2019-01-01}, journal = {Artificial intelligence in medicine}, volume = {99}, note = {DOI: 10.1016/j.artmed.2019.06.006}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Renaux, Alexandre; Papadimitriou, Sofia; Versbraegen, Nassim; Nachtegael, Charlotte; Boutry, Simon; Nowé, Ann; Smits, Guillaume; Lenaerts, Tom ORVAL: a novel platform for the prediction and exploration of disease-causing oligogenic variant combinations. Journal Article Nucleic acids research, 47 (W1), pp. W93-W98, 2019, (DOI: 10.1093/nar/gkz437). @article{info:hdl:2013/289958, title = {ORVAL: a novel platform for the prediction and exploration of disease-causing oligogenic variant combinations.}, author = {Alexandre Renaux and Sofia Papadimitriou and Nassim Versbraegen and Charlotte Nachtegael and Simon Boutry and Ann Nowé and Guillaume Smits and Tom Lenaerts}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/289958}, year = {2019}, date = {2019-01-01}, journal = {Nucleic acids research}, volume = {47}, number = {W1}, pages = {W93-W98}, note = {DOI: 10.1093/nar/gkz437}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Papadimitriou, Sofia; Gazzo, Andrea; Versbraegen, Nassim; Nachtegael, Charlotte; Aerts, Jan; Moreau, Yves; Dooren, Sonia Van; Nowe, Ann; Smits, Guillaume; Lenaerts, Tom Predicting disease-causing variant combinations Journal Article Proceedings of the National Academy of Sciences of the United States of America, 116 (24), pp. 11878-11887, 2019, (DOI: 10.1073/pnas.1815601116). @article{info:hdl:2013/289724, title = {Predicting disease-causing variant combinations}, author = {Sofia Papadimitriou and Andrea Gazzo and Nassim Versbraegen and Charlotte Nachtegael and Jan Aerts and Yves Moreau and Sonia Van Dooren and Ann Nowe and Guillaume Smits and Tom Lenaerts}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/289724}, year = {2019}, date = {2019-01-01}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, volume = {116}, number = {24}, pages = {11878-11887}, note = {DOI: 10.1073/pnas.1815601116}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Bontempi, Gianluca The Induction Problem: A Machine Learning Vindication Argument Journal Article Lecture notes in computer science, 11943 LNCS , pp. 232-243, 2019, (DOI: 10.1007/978-3-030-37599-7_20). @article{info:hdl:2013/303320, title = {The Induction Problem: A Machine Learning Vindication Argument}, author = {Gianluca Bontempi}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/303320}, year = {2019}, date = {2019-01-01}, journal = {Lecture notes in computer science}, volume = {11943 LNCS}, pages = {232-243}, note = {DOI: 10.1007/978-3-030-37599-7_20}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Carcillo, Fabrizio; "e, Yann-A; Caelen, Olivier; Kessaci, Yacine; Oblé, Frédéric; Bontempi, Gianluca Combining unsupervised and supervised learning in credit card fraud detection Journal Article Information sciences, 2019, (DOI: 10.1016/j.ins.2019.05.042). @article{info:hdl:2013/289125, title = {Combining unsupervised and supervised learning in credit card fraud detection}, author = {Fabrizio Carcillo and Yann-A{"e}l Le Borgne and Olivier Caelen and Yacine Kessaci and Frédéric Oblé and Gianluca Bontempi}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/289125}, year = {2019}, date = {2019-01-01}, journal = {Information sciences}, note = {DOI: 10.1016/j.ins.2019.05.042}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Bontempi, Gianluca Comments on M4 competition Journal Article International journal of forecasting, 2019, (DOI: 10.1016/j.ijforecast.2019.03.028). @article{info:hdl:2013/292419, title = {Comments on M4 competition}, author = {Gianluca Bontempi}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/292419}, year = {2019}, date = {2019-01-01}, journal = {International journal of forecasting}, note = {DOI: 10.1016/j.ijforecast.2019.03.028}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Saykali, Bechara; Nahaboo, Wallis; Mathiah, Navrita; Racu, Marie-Lucie; Defrance, Matthieu; Migeotte, Isabelle Distinct mesoderm migration phenotypes in extra-embryonic and embryonic regions of the early mouse embryo Journal Article eLife, 8 , 2019, (DOI: 10.7554/eLife.42434.001). @article{info:hdl:2013/282177, title = {Distinct mesoderm migration phenotypes in extra-embryonic and embryonic regions of the early mouse embryo}, author = {Bechara Saykali and Wallis Nahaboo and Navrita Mathiah and Marie-Lucie Racu and Matthieu Defrance and Isabelle Migeotte}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/282177}, year = {2019}, date = {2019-01-01}, journal = {eLife}, volume = {8}, note = {DOI: 10.7554/eLife.42434.001}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Mounir, Mohamed; Lucchetta, Marta; Silva, Tiago Henrique Da T C; Olsen, Catharina; Bontempi, Gianluca; Chen, Xi; Noushmehr, Houtan; Colaprico, Antonio; Papaleo, Elena New functionalities in the TCGAbiolinks package for the study and integration of cancer data from GDC and GTEx Journal Article PLoS computational biology, 15 (3), pp. e1006701, 2019, (DOI: 10.1371/journal.pcbi.1006701). @article{info:hdl:2013/286948, title = {New functionalities in the TCGAbiolinks package for the study and integration of cancer data from GDC and GTEx}, author = {Mohamed Mounir and Marta Lucchetta and Tiago Henrique Da T C Silva and Catharina Olsen and Gianluca Bontempi and Xi Chen and Houtan Noushmehr and Antonio Colaprico and Elena Papaleo}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/286948}, year = {2019}, date = {2019-01-01}, journal = {PLoS computational biology}, volume = {15}, number = {3}, pages = {e1006701}, note = {DOI: 10.1371/journal.pcbi.1006701}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Libin, Pieter; Versbraegen, Nassim; Abecasis, Ana A B; Gomes, Perpétua; Lenaerts, Tom; Nowe, Ann Towards a phylogenetic measure to quantify HIV incidence Journal Article CEUR Workshop Proceedings, 2491 , 2019, (Language of publication: en). @article{info:hdl:2013/296964, title = {Towards a phylogenetic measure to quantify HIV incidence}, author = {Pieter Libin and Nassim Versbraegen and Ana A B Abecasis and Perpétua Gomes and Tom Lenaerts and Ann Nowe}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/296964}, year = {2019}, date = {2019-01-01}, journal = {CEUR Workshop Proceedings}, volume = {2491}, note = {Language of publication: en}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Verhelst, Theo; Caelen, Olivier; Dewitte, Jean Christophe; Lebichot, Bertrand; Bontempi, Gianluca Understanding telecom customer churn with machine learning: From prediction to causal inference Journal Article CEUR Workshop Proceedings, 2491 , 2019, (Language of publication: en). @article{info:hdl:2013/296511, title = {Understanding telecom customer churn with machine learning: From prediction to causal inference}, author = {Theo Verhelst and Olivier Caelen and Jean Christophe Dewitte and Bertrand Lebichot and Gianluca Bontempi}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/296511}, year = {2019}, date = {2019-01-01}, journal = {CEUR Workshop Proceedings}, volume = {2491}, note = {Language of publication: en}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Coppens, Youri; Efthymiadis, Kyriakos; Lenaerts, Tom; Nowé, Ann Distilling Deep Reinforcement Learning Policies in Soft Decision Trees Inproceedings Miller, Tim; Weber, Rosina; Magazzeni, Daniele (Ed.): Proceedings of the IJCAI 2019 Workshop on Explainable Artificial Intelligence, 2019, (Conference: (Macau, China)). @inproceedings{info:hdl:2013/302065, title = {Distilling Deep Reinforcement Learning Policies in Soft Decision Trees}, author = {Youri Coppens and Kyriakos Efthymiadis and Tom Lenaerts and Ann Nowé}, editor = {Tim Miller and Rosina Weber and Daniele Magazzeni}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/302065}, year = {2019}, date = {2019-01-01}, booktitle = {Proceedings of the IJCAI 2019 Workshop on Explainable Artificial Intelligence}, note = {Conference: (Macau, China)}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Stefani, Jacopo De; Caelen, Olivier; Hattab, Dalila; "e, Yann-A; Bontempi, Gianluca A Multivariate and Multi-step Ahead Machine Learning Approach to Traditional and Cryptocurrencies Volatility Forecasting Inproceedings ECML PKDD 2018 Workshops, Springer, 2019, (Conference: ECML-PKDD 2018(Dublin)). @inproceedings{info:hdl:2013/284007, title = {A Multivariate and Multi-step Ahead Machine Learning Approach to Traditional and Cryptocurrencies Volatility Forecasting}, author = {Jacopo De Stefani and Olivier Caelen and Dalila Hattab and Yann-A{"e}l Le Borgne and Gianluca Bontempi}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/284007}, year = {2019}, date = {2019-01-01}, booktitle = {ECML PKDD 2018 Workshops}, publisher = {Springer}, series = {Lecture Notes in Computer Science, 11054}, note = {Conference: ECML-PKDD 2018(Dublin)}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Abels, Axel; Roijers, Diederik D M; Lenaerts, Tom; Nowe, Ann; Steckelmacher, Denis Dynamic Weights in Multi-Objective Deep Reinforcement Learning Inproceedings Proceedings of the 36th International Conference on Machine Learning, pp. 11-20, PMLR, 2019, (Language of publication: en). @inproceedings{info:hdl:2013/291979, title = {Dynamic Weights in Multi-Objective Deep Reinforcement Learning}, author = {Axel Abels and Diederik D M Roijers and Tom Lenaerts and Ann Nowe and Denis Steckelmacher}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/291979}, year = {2019}, date = {2019-01-01}, booktitle = {Proceedings of the 36th International Conference on Machine Learning}, pages = {11-20}, publisher = {PMLR}, series = {Proceedings of Machine Learning Research}, note = {Language of publication: en}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Han, The Anh T A H; Pereira, Luís Moniz; Lenaerts, Tom Modelling and influencing the AI bidding War: A research agenda Inproceedings Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, Association for Computing Machinery, 2019, (Conference: AAAI/ACM Conference on AI, Ethics, and Society(Honolulu, HI, USA)). @inproceedings{info:hdl:2013/314481, title = {Modelling and influencing the AI bidding War: A research agenda}, author = {The Anh T A H Han and Luís Moniz Pereira and Tom Lenaerts}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/314481}, year = {2019}, date = {2019-01-01}, booktitle = {Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society}, publisher = {Association for Computing Machinery}, series = {AIES'19 series}, note = {Conference: AAAI/ACM Conference on AI, Ethics, and Society(Honolulu, HI, USA)}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Stefani, Jacopo De; Bontempi, Gianluca; Caelen, Olivier; Hattab, Dalila SYSTEM AND METHOD FOR MANAGING RISKS IN A PROCESS Miscellaneous 2019, (Language of publication: fr). @misc{info:hdl:2013/283233, title = {SYSTEM AND METHOD FOR MANAGING RISKS IN A PROCESS}, author = {Jacopo De Stefani and Gianluca Bontempi and Olivier Caelen and Dalila Hattab}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/283233}, year = {2019}, date = {2019-01-01}, note = {Language of publication: fr}, keywords = {}, pubstate = {published}, tppubtype = {misc} } |
2018 |
`e, Nathaniel Mon P; Lenaerts, Tom; Pacheco, Jorge M J M; Dingli, David Evolutionary Dynamics of Paroxysmal Nocturnal Hemoglobinuria Journal Article PLoS computational biology, 2018, (Language of publication: en). @article{info:hdl:2013/267360, title = {Evolutionary Dynamics of Paroxysmal Nocturnal Hemoglobinuria}, author = {Nathaniel Mon P{`e}re and Tom Lenaerts and Jorge M J M Pacheco and David Dingli}, url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/267360/3/MonPereEtAlPLoSCB.docx}, year = {2018}, date = {2018-01-01}, journal = {PLoS computational biology}, note = {Language of publication: en}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Raimondi, Daniele; Orlando, Gabriele; Tabaro, Francesco; Lenaerts, Tom; Rooman, Marianne; Moreau, Yves; Vranken, Wim F Large-scale in-silico statistical mutagenesis analysis sheds light on the deleteriousness landscape of the human proteome Journal Article Scientific reports, 2018, (Language of publication: en). @article{info:hdl:2013/273192, title = {Large-scale in-silico statistical mutagenesis analysis sheds light on the deleteriousness landscape of the human proteome}, author = {Daniele Raimondi and Gabriele Orlando and Francesco Tabaro and Tom Lenaerts and Marianne Rooman and Yves Moreau and Wim F Vranken}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/273192}, year = {2018}, date = {2018-01-01}, journal = {Scientific reports}, note = {Language of publication: en}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Skiba, Grażyna; Starzec, Mateusz; Byrski, Aleksander; Rycerz, Katarzyna; Kisiel-Dorohinicki, Marek; Turek, Wojciech; Krzywicki, Daniel; Lenaerts, Tom; Burguillo, Juan Carlos Flexible asynchronous simulation of iterated prisoner's dilemma based on actor model Journal Article Simulation modelling practice and theory, 83 , pp. 75-92, 2018, (DOI: 10.1016/j.simpat.2017.12.010). @article{info:hdl:2013/272556, title = {Flexible asynchronous simulation of iterated prisoner's dilemma based on actor model}, author = {Grażyna Skiba and Mateusz Starzec and Aleksander Byrski and Katarzyna Rycerz and Marek Kisiel-Dorohinicki and Wojciech Turek and Daniel Krzywicki and Tom Lenaerts and Juan Carlos Burguillo}, url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/272556/1/Elsevier_256183.pdf}, year = {2018}, date = {2018-01-01}, journal = {Simulation modelling practice and theory}, volume = {83}, pages = {75-92}, abstract = {The wide range of applications of the Iterated prisoner's dilemma (IPD) game made it a popular subject of study for the research community. As a consequence, numerous experiments have been conducted by researchers along the last decades. However, topics related with scaling simulation leveraging existing HPC infrastructure in the field of IPD did not always play a relevant role in such experimental work. The main contribution of this paper is a new simulation framework, based on asynchronous communication and its implementation oriented to distributed environments. Such framework is based on the modern Akka actor platform, that supports concurrent, distributed and resilient message-driven simulations; which are exemplified over the IPD game as a case study. We also present several interesting results regarding the introduction of asynchrony into the IPD simulation in order to obtain an efficient framework, so the whole simulation becomes scalable when using HPC facilities. The influence of asynchrony on the algorithm itself is also discussed, and the results show that it does not hamper the simulation.}, note = {DOI: 10.1016/j.simpat.2017.12.010}, keywords = {}, pubstate = {published}, tppubtype = {article} } The wide range of applications of the Iterated prisoner's dilemma (IPD) game made it a popular subject of study for the research community. As a consequence, numerous experiments have been conducted by researchers along the last decades. However, topics related with scaling simulation leveraging existing HPC infrastructure in the field of IPD did not always play a relevant role in such experimental work. The main contribution of this paper is a new simulation framework, based on asynchronous communication and its implementation oriented to distributed environments. Such framework is based on the modern Akka actor platform, that supports concurrent, distributed and resilient message-driven simulations; which are exemplified over the IPD game as a case study. We also present several interesting results regarding the introduction of asynchrony into the IPD simulation in order to obtain an efficient framework, so the whole simulation becomes scalable when using HPC facilities. The influence of asynchrony on the algorithm itself is also discussed, and the results show that it does not hamper the simulation. |
Kieken, Fabien; Loth, Karine; van Nuland, Nico N A J; Tompa, Peter; Lenaerts, Tom Chemical shift assignments of the partially deuterated Fyn SH2–SH3 domain Journal Article Biomolecular N M R Assignments, 12 (1), pp. 117-122, 2018, (DOI: 10.1007/s12104-017-9792-1). @article{info:hdl:2013/272541, title = {Chemical shift assignments of the partially deuterated Fyn SH2–SH3 domain}, author = {Fabien Kieken and Karine Loth and Nico N A J van Nuland and Peter Tompa and Tom Lenaerts}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/272541}, year = {2018}, date = {2018-01-01}, journal = {Biomolecular N M R Assignments}, volume = {12}, number = {1}, pages = {117-122}, abstract = {Src Homology 2 and 3 (SH2 and SH3) are two key protein interaction modules involved in regulating the activity of many proteins such as tyrosine kinases and phosphatases by respective recognition of phosphotyrosine and proline-rich regions. In the Src family kinases, the inactive state of the protein is the direct result of the interaction of the SH2 and the SH3 domain with intra-molecular regions, leading to a closed structure incompetent with substrate modification. Here, we report the 1H, 15N and 13C backbone- and side-chain chemical shift assignments of the partially deuterated Fyn SH3–SH2 domain and structural differences between tandem and single domains. The BMRB accession number is 27165.}, note = {DOI: 10.1007/s12104-017-9792-1}, keywords = {}, pubstate = {published}, tppubtype = {article} } Src Homology 2 and 3 (SH2 and SH3) are two key protein interaction modules involved in regulating the activity of many proteins such as tyrosine kinases and phosphatases by respective recognition of phosphotyrosine and proline-rich regions. In the Src family kinases, the inactive state of the protein is the direct result of the interaction of the SH2 and the SH3 domain with intra-molecular regions, leading to a closed structure incompetent with substrate modification. Here, we report the 1H, 15N and 13C backbone- and side-chain chemical shift assignments of the partially deuterated Fyn SH3–SH2 domain and structural differences between tandem and single domains. The BMRB accession number is 27165. |
Byrski, Aleksander; Świderska, Ewelina; Łasisz, Jakub; Kisiel-Dorohinicki, Marek; Lenaerts, Tom; Samson, Dana; Indurkhya, Bipin Emergence of population structure in socio-cognitively inspired ant colony optimization Journal Article Computer Science, 19 (1), pp. 81-98, 2018, (DOI: 10.7494/csci.2018.19.1.2594). @article{info:hdl:2013/270586, title = {Emergence of population structure in socio-cognitively inspired ant colony optimization}, author = {Aleksander Byrski and Ewelina Świderska and Jakub Łasisz and Marek Kisiel-Dorohinicki and Tom Lenaerts and Dana Samson and Bipin Indurkhya}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/270586}, year = {2018}, date = {2018-01-01}, journal = {Computer Science}, volume = {19}, number = {1}, pages = {81-98}, abstract = {A metaheuristic proposed by us recently, Ant Colony Optimization (ACO) hybridized with socio-cognitive inspirations, turned out to generate interesting results when compared to classic ACO. Even though it does not always find better solutions to the considered problems, it usually finds sub-optimal solutions. Moreover, instead of a trial-and-error approach to configure the parameters of the ant species in the population, the actual structure of the population emerges from a predefined species-to-species ant migration strategies in our approach. Experimental results of our approach are compared to classic ACO and selected socio-cognitive versions of this algorithm.}, note = {DOI: 10.7494/csci.2018.19.1.2594}, keywords = {}, pubstate = {published}, tppubtype = {article} } A metaheuristic proposed by us recently, Ant Colony Optimization (ACO) hybridized with socio-cognitive inspirations, turned out to generate interesting results when compared to classic ACO. Even though it does not always find better solutions to the considered problems, it usually finds sub-optimal solutions. Moreover, instead of a trial-and-error approach to configure the parameters of the ant species in the population, the actual structure of the population emerges from a predefined species-to-species ant migration strategies in our approach. Experimental results of our approach are compared to classic ACO and selected socio-cognitive versions of this algorithm. |
de Bony, Eric James; Bizet, Martin; Grembergen, Olivier Van; Hassabi, Bouchra; Calonne, Emilie; Putmans, Pascale; Bontempi, Gianluca; cc, Fran Comprehensive identification of long noncoding RNAs in colorectal cancer Journal Article Oncotarget, 9 (45), pp. 27605-27629, 2018, (DOI: 10.18632/oncotarget.25218). @article{info:hdl:2013/278063, title = {Comprehensive identification of long noncoding RNAs in colorectal cancer}, author = {Eric James de Bony and Martin Bizet and Olivier Van Grembergen and Bouchra Hassabi and Emilie Calonne and Pascale Putmans and Gianluca Bontempi and Fran{cc}ois Fuks}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/278063}, year = {2018}, date = {2018-01-01}, journal = {Oncotarget}, volume = {9}, number = {45}, pages = {27605-27629}, abstract = {Colorectal cancer (CRC) is one of the most common cancers in humans and a leading cause of cancer-related deaths worldwide. As in the case of other cancers, CRC heterogeneity leads to a wide range of clinical outcomes and complicates therapy. Over the years, multiple factors have emerged as markers of CRC heterogeneity, improving tumor classification and selection of therapeutic strategies. Understanding the molecular mechanisms underlying this heterogeneity remains a major challenge. A considerable research effort is therefore devoted to identifying additional features of colorectal tumors, in order to better understand CRC etiology and to multiply therapeutic avenues. Recently, long noncoding RNAs (lncRNAs) have emerged as important players in physiological and pathological processes, including CRC. Here we looked for lncRNAs that might contribute to the various colorectal tumor phenotypes. We thus monitored the expression of 4898 lncRNA genes across 566 CRC samples and identified 282 lncRNAs reflecting CRC heterogeneity. We then inferred potential functions of these lncRNAs. Our results highlight lncRNAs that may participate in the major processes altered in distinct CRC cases, such as WNT/β-catenin and TGF-β signaling, immunity, the epithelial-to-mesenchymal transition (EMT), and angiogenesis. For several candidates, we provide experimental evidence supporting our functional predictions that they may be involved in the cell cycle or the EMT. Overall, our work identifies lncRNAs associated with key CRC characteristics and provides insights into their respective functions. Our findings constitute a further step towards understanding the contribution of lncRNAs to CRC heterogeneity. They may open new therapeutic opportunities.}, note = {DOI: 10.18632/oncotarget.25218}, keywords = {}, pubstate = {published}, tppubtype = {article} } Colorectal cancer (CRC) is one of the most common cancers in humans and a leading cause of cancer-related deaths worldwide. As in the case of other cancers, CRC heterogeneity leads to a wide range of clinical outcomes and complicates therapy. Over the years, multiple factors have emerged as markers of CRC heterogeneity, improving tumor classification and selection of therapeutic strategies. Understanding the molecular mechanisms underlying this heterogeneity remains a major challenge. A considerable research effort is therefore devoted to identifying additional features of colorectal tumors, in order to better understand CRC etiology and to multiply therapeutic avenues. Recently, long noncoding RNAs (lncRNAs) have emerged as important players in physiological and pathological processes, including CRC. Here we looked for lncRNAs that might contribute to the various colorectal tumor phenotypes. We thus monitored the expression of 4898 lncRNA genes across 566 CRC samples and identified 282 lncRNAs reflecting CRC heterogeneity. We then inferred potential functions of these lncRNAs. Our results highlight lncRNAs that may participate in the major processes altered in distinct CRC cases, such as WNT/β-catenin and TGF-β signaling, immunity, the epithelial-to-mesenchymal transition (EMT), and angiogenesis. For several candidates, we provide experimental evidence supporting our functional predictions that they may be involved in the cell cycle or the EMT. Overall, our work identifies lncRNAs associated with key CRC characteristics and provides insights into their respective functions. Our findings constitute a further step towards understanding the contribution of lncRNAs to CRC heterogeneity. They may open new therapeutic opportunities. |
Ioannidis, J P A; Bhattacharya, S; Evers, J L H; Veen, Der F V; Somigliana, E; Barratt, C L R; Bontempi, Gianluca; Baird, D T; Crosignani, P; Devroey, P; Diedrich, Klaus; Farquharson, R G; Fraser, L R; Geraedts, Joep Pm M; Gianaroli, Luca; Vecchia, La C; Magli, C; Negri, E; Sunde, A; Tapanainen, J S; Tarlatzis, Basil; Steirteghem, A V; Veiga, A Protect us from poor-quality medical research Journal Article Human reproduction, 33 (5), pp. 770-776, 2018, (DOI: 10.1093/humrep/dey056). @article{info:hdl:2013/272828, title = {Protect us from poor-quality medical research}, author = {J P A Ioannidis and S Bhattacharya and J L H Evers and F V Der Veen and E Somigliana and C L R Barratt and Gianluca Bontempi and D T Baird and P Crosignani and P Devroey and Klaus Diedrich and R G Farquharson and L R Fraser and Joep Pm M Geraedts and Luca Gianaroli and C La Vecchia and C Magli and E Negri and A Sunde and J S Tapanainen and Basil Tarlatzis and A V Steirteghem and A Veiga}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/272828}, year = {2018}, date = {2018-01-01}, journal = {Human reproduction}, volume = {33}, number = {5}, pages = {770-776}, abstract = {Much of the published medical research is apparently flawed, cannot be replicated and/or has limited or no utility. This article presents an overview of the current landscape of biomedical research, identifies problems associated with common study designs and considers potential solutions. Randomized clinical trials, observational studies, systematic reviews and meta-analyses are discussed in terms of their inherent limitations and potential ways of improving their conduct, analysis and reporting. The current emphasis on statistical significance needs to be replaced by sound design, transparency and willingness to share data with a clear commitment towards improving the quality and utility of clinical research.}, note = {DOI: 10.1093/humrep/dey056}, keywords = {}, pubstate = {published}, tppubtype = {article} } Much of the published medical research is apparently flawed, cannot be replicated and/or has limited or no utility. This article presents an overview of the current landscape of biomedical research, identifies problems associated with common study designs and considers potential solutions. Randomized clinical trials, observational studies, systematic reviews and meta-analyses are discussed in terms of their inherent limitations and potential ways of improving their conduct, analysis and reporting. The current emphasis on statistical significance needs to be replaced by sound design, transparency and willingness to share data with a clear commitment towards improving the quality and utility of clinical research. |
Trepo, Eric; Goossens, Nicolas; Fujiwara, Naoto; Song, Won-Min; Colaprico, Antonio; Marot, Astrid; Spahr, Laurent; Demetter, Pieter; Sempoux, Christine; Im, Gene Y; Saldarriaga, Joan; Gustot, Thierry; `e, Jacques Devi; Thung, Swan SN; Minsart, Charlotte; Serste, Thomas; Bontempi, Gianluca; Abdelrahman, Karim; Henrion, Jean; Degré, Delphine; Lucidi, Valerio; Rubbia-Brandt, Laura; Nair, Venugopalan D; Moreno, Christophe; Deltenre, Pierre; Hoshida, Yujin; Franchimont, Denis Gastroenterology, 154 (4), pp. 965-975, 2018, (DOI: 10.1053/j.gastro.2017.10.048). @article{info:hdl:2013/269084, title = {Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis}, author = {Eric Trepo and Nicolas Goossens and Naoto Fujiwara and Won-Min Song and Antonio Colaprico and Astrid Marot and Laurent Spahr and Pieter Demetter and Christine Sempoux and Gene Y Im and Joan Saldarriaga and Thierry Gustot and Jacques Devi{`e}re and Swan SN Thung and Charlotte Minsart and Thomas Serste and Gianluca Bontempi and Karim Abdelrahman and Jean Henrion and Delphine Degré and Valerio Lucidi and Laura Rubbia-Brandt and Venugopalan D Nair and Christophe Moreno and Pierre Deltenre and Yujin Hoshida and Denis Franchimont}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/269084}, year = {2018}, date = {2018-01-01}, journal = {Gastroenterology}, volume = {154}, number = {4}, pages = {965-975}, abstract = {Background & Aims: Patients with severe alcoholic hepatitis (AH) have a high risk of death within 90 days. Corticosteroids, which can cause severe adverse events, are the only treatment that increases short-term survival. It is a challenge to predict outcomes of patients with severe AH. Therefore, we developed a scoring system to predict patient survival, integrating baseline molecular and clinical variables. Methods: We obtained fixed liver biopsy samples from 71 consecutive patients diagnosed with severe AH and treated with corticosteroids from July 2006 through December 2013 in Brussels, Belgium (derivation cohort). Gene expression patterns were analyzed by microarrays and clinical data were collected for 180 days. We identified gene expression signatures and clinical data that are associated with survival without liver transplantation at 90 and 180 days after initiation of corticosteroid therapy. Findings were validated using liver biopsies from 48 consecutive patients with severe AH treated with corticosteroids, collected from March 2010 through February 2015 at hospitals in Belgium and Switzerland (validation cohort 1) and in liver biopsies from 20 patients (9 received corticosteroid treatment), collected from January 2012 through May 2015 in the United States (validation cohort 2). Results: We integrated data on expression patterns of 123 genes and the model for end-stage liver disease (MELD) scores to assign patients to groups with poor survival (29% survived 90 days and 26% survived 180 days) and good survival (76% survived 90 days and 65% survived 180 days) (P <.001) in the derivation cohort. We named this assignment system the gene signature–MELD (gs-MELD) score. In validation cohort 1, the gs-MELD score discriminated patients with poor survival (43% survived 90 days) from those with good survival (96% survived 90 days) (P <.001). The gs-MELD score also discriminated between patients with a poor survival at 180 days (34% survived) and a good survival at 180 days (84% survived) (P <.001). The time-dependent area under the receiver operator characteristic curve for the score was 0.86 (95% confidence interval 0.73–0.99) for survival at 90 days, and 0.83 (95% confidence interval 0.71–0.96) for survival at 180 days. This score outperformed other clinical models to predict survival of patients with severe AH in validation cohort 1. In validation cohort 2, the gs-MELD discriminated patients with a poor survival at 90 days (12% survived) from those with a good survival at 90 days (100%) (P <.001). Conclusions: We integrated data on baseline liver gene expression pattern and the MELD score to create the gs-MELD scoring system, which identifies patients with severe AH, treated or not with corticosteroids, most and least likely to survive for 90 and 180 days.}, note = {DOI: 10.1053/j.gastro.2017.10.048}, keywords = {}, pubstate = {published}, tppubtype = {article} } Background & Aims: Patients with severe alcoholic hepatitis (AH) have a high risk of death within 90 days. Corticosteroids, which can cause severe adverse events, are the only treatment that increases short-term survival. It is a challenge to predict outcomes of patients with severe AH. Therefore, we developed a scoring system to predict patient survival, integrating baseline molecular and clinical variables. Methods: We obtained fixed liver biopsy samples from 71 consecutive patients diagnosed with severe AH and treated with corticosteroids from July 2006 through December 2013 in Brussels, Belgium (derivation cohort). Gene expression patterns were analyzed by microarrays and clinical data were collected for 180 days. We identified gene expression signatures and clinical data that are associated with survival without liver transplantation at 90 and 180 days after initiation of corticosteroid therapy. Findings were validated using liver biopsies from 48 consecutive patients with severe AH treated with corticosteroids, collected from March 2010 through February 2015 at hospitals in Belgium and Switzerland (validation cohort 1) and in liver biopsies from 20 patients (9 received corticosteroid treatment), collected from January 2012 through May 2015 in the United States (validation cohort 2). Results: We integrated data on expression patterns of 123 genes and the model for end-stage liver disease (MELD) scores to assign patients to groups with poor survival (29% survived 90 days and 26% survived 180 days) and good survival (76% survived 90 days and 65% survived 180 days) (P <.001) in the derivation cohort. We named this assignment system the gene signature–MELD (gs-MELD) score. In validation cohort 1, the gs-MELD score discriminated patients with poor survival (43% survived 90 days) from those with good survival (96% survived 90 days) (P <.001). The gs-MELD score also discriminated between patients with a poor survival at 180 days (34% survived) and a good survival at 180 days (84% survived) (P <.001). The time-dependent area under the receiver operator characteristic curve for the score was 0.86 (95% confidence interval 0.73–0.99) for survival at 90 days, and 0.83 (95% confidence interval 0.71–0.96) for survival at 180 days. This score outperformed other clinical models to predict survival of patients with severe AH in validation cohort 1. In validation cohort 2, the gs-MELD discriminated patients with a poor survival at 90 days (12% survived) from those with a good survival at 90 days (100%) (P <.001). Conclusions: We integrated data on baseline liver gene expression pattern and the MELD score to create the gs-MELD scoring system, which identifies patients with severe AH, treated or not with corticosteroids, most and least likely to survive for 90 and 180 days. |
Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Bontempi, Gianluca; Mauri, Giancarlo; Castiglioni, Isabella In-silico integration approach to identify a key miRNA regulating a gene network in aggressive prostate cancer Journal Article International journal of molecular sciences, 19 (3), 2018, (DOI: 10.3390/ijms19030910). @article{info:hdl:2013/270452, title = {In-silico integration approach to identify a key miRNA regulating a gene network in aggressive prostate cancer}, author = {Claudia Cava and Gloria Bertoli and Antonio Colaprico and Gianluca Bontempi and Giancarlo Mauri and Isabella Castiglioni}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/270452}, year = {2018}, date = {2018-01-01}, journal = {International journal of molecular sciences}, volume = {19}, number = {3}, abstract = {Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC.}, note = {DOI: 10.3390/ijms19030910}, keywords = {}, pubstate = {published}, tppubtype = {article} } Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. |
Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis Journal Article BMC genomics, 19 (1), 2018, (DOI: 10.1186/s12864-017-4423-x). @article{info:hdl:2013/268430, title = {Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis}, author = {Claudia Cava and Gloria Bertoli and Antonio Colaprico and Catharina Olsen and Gianluca Bontempi and Isabella Castiglioni}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/268430}, year = {2018}, date = {2018-01-01}, journal = {BMC genomics}, volume = {19}, number = {1}, abstract = {Background: Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. Results: We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Conclusions: Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.}, note = {DOI: 10.1186/s12864-017-4423-x}, keywords = {}, pubstate = {published}, tppubtype = {article} } Background: Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. Results: We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Conclusions: Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways. |
Reggiani, Claudio; "e, Yann-A; Bontempi, Gianluca Feature selection in high-dimensional dataset using MapReduce Journal Article Communications in computer and information science, 823 , pp. 101-115, 2018, (DOI: 10.1007/978-3-319-76892-2_8). @article{info:hdl:2013/269455, title = {Feature selection in high-dimensional dataset using MapReduce}, author = {Claudio Reggiani and Yann-A{"e}l Le Borgne and Gianluca Bontempi}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/269455}, year = {2018}, date = {2018-01-01}, journal = {Communications in computer and information science}, volume = {823}, pages = {101-115}, abstract = {This paper describes a distributed MapReduce implementation of the minimum Redundancy Maximum Relevance algorithm, a popular feature selection method in bioinformatics and network inference problems. The proposed approach handles both tall/narrow and wide/short datasets. We further provide an open source implementation based on Hadoop/Spark, and illustrate its scalability on datasets involving millions of observations or features.}, note = {DOI: 10.1007/978-3-319-76892-2_8}, keywords = {}, pubstate = {published}, tppubtype = {article} } This paper describes a distributed MapReduce implementation of the minimum Redundancy Maximum Relevance algorithm, a popular feature selection method in bioinformatics and network inference problems. The proposed approach handles both tall/narrow and wide/short datasets. We further provide an open source implementation based on Hadoop/Spark, and illustrate its scalability on datasets involving millions of observations or features. |
Jansen, Maarten Sparsity on nonequispaced knots with B-spline wavelets Miscellaneous 2018, (Conference: Seminar, University of Hannover). @misc{info:hdl:2013/280770, title = {Sparsity on nonequispaced knots with B-spline wavelets}, author = {Maarten Jansen}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/280770}, year = {2018}, date = {2018-01-01}, note = {Conference: Seminar, University of Hannover}, keywords = {}, pubstate = {published}, tppubtype = {misc} } |
Jansen, Maarten A sparse variable selection approach in multiscale local polynomial density estimation Miscellaneous 2018, (Conference: International conference on Computational Statistics (23: 2018: Iasi, Romania)). @misc{info:hdl:2013/280735, title = {A sparse variable selection approach in multiscale local polynomial density estimation}, author = {Maarten Jansen}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/280735}, year = {2018}, date = {2018-01-01}, note = {Conference: International conference on Computational Statistics (23: 2018: Iasi, Romania)}, keywords = {}, pubstate = {published}, tppubtype = {misc} } |
Jansen, Maarten Density estimation using multiscale local polynomial transforms Miscellaneous 2018, (Conference: Conference of the International Society of Nonparametric Statistics (2018: Salerno, Italy)). @misc{info:hdl:2013/280737, title = {Density estimation using multiscale local polynomial transforms}, author = {Maarten Jansen}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/280737}, year = {2018}, date = {2018-01-01}, note = {Conference: Conference of the International Society of Nonparametric Statistics (2018: Salerno, Italy)}, keywords = {}, pubstate = {published}, tppubtype = {misc} } |
Jansen, Maarten Multiscale Local Polynomial transforms for use in density estimation and exponential models Miscellaneous 2018, (Conference: Workshop on Statistical Signal Processing 2018 (2018: Lancaster, UK)). @misc{info:hdl:2013/280738, title = {Multiscale Local Polynomial transforms for use in density estimation and exponential models}, author = {Maarten Jansen}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/280738}, year = {2018}, date = {2018-01-01}, note = {Conference: Workshop on Statistical Signal Processing 2018 (2018: Lancaster, UK)}, keywords = {}, pubstate = {published}, tppubtype = {misc} } |
Abels, Axel; Roijers, Diederik D M; Lenaerts, Tom Dynamic weights in multi-objective deep reinforcement learning Journal Article BNAIC, pp. 1-2, 2018, (Language of publication: en). @article{info:hdl:2013/296973, title = {Dynamic weights in multi-objective deep reinforcement learning}, author = {Axel Abels and Diederik D M Roijers and Tom Lenaerts}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/296973}, year = {2018}, date = {2018-01-01}, journal = {BNAIC}, pages = {1-2}, note = {Language of publication: en}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Raimondi, Daniele; Orlando, Gabriele; Tabaro, Francesco; Lenaerts, Tom; Rooman, Marianne; Moreau, Yves; Vranken, Wim F Large-scale in-silico statistical mutagenesis analysis sheds light on the deleteriousness landscape of the human proteome. Journal Article Scientific reports, 8 (1), pp. 16980, 2018, (DOI: 10.1038/s41598-018-34959-7). @article{info:hdl:2013/283645, title = {Large-scale in-silico statistical mutagenesis analysis sheds light on the deleteriousness landscape of the human proteome.}, author = {Daniele Raimondi and Gabriele Orlando and Francesco Tabaro and Tom Lenaerts and Marianne Rooman and Yves Moreau and Wim F Vranken}, url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/283645}, year = {2018}, date = {2018-01-01}, journal = {Scientific reports}, volume = {8}, number = {1}, pages = {16980}, note = {DOI: 10.1038/s41598-018-34959-7}, keywords = {}, pubstate = {published}, tppubtype = {article} } |